Top Data & Analytics Jobs

The EO Imagery Analyst will provide geospatial and imagery analysis to improve data operations for ML algorithm testing, working with EO imagery products and metadata.

The Geospatial SAR Imagery Analyst Scientist analyzes SAR data to improve machine learning algorithms, curating imagery for data sets and recommending strategies for data gaps.

The EO Imagery Geospatial Analyst/Scientist provides geospatial expertise, conducts assessments, analyzes data formats, and supports ML algorithm testing.

Responsible for validating market risk models and ensuring their accuracy. Engage with various stakeholders, communicate findings, and maintain model integrity while leveraging innovative analytical technologies.

Senior Solution Architect responsible for strategy, solution and data architecture across application, platform, and data domains. Designs scalable architectures, data models, integration patterns, and data platforms (warehouses, lakes, streaming, cloud). Partners with business and engineering teams to ensure architectures meet functional, nonfunctional, governance, security, and regulatory requirements while enabling analytics, AI/ML, and transformation.

Lead data analysis and automation tasks: gather and map business requirements, coordinate with upstream systems, participate in Scrum/planning, support production issues, develop information systems, advise users on data manipulation and analytics, implement data management technologies, and research customer needs.

Lead analytics and machine-learning efforts to prevent point-of-sale fraud: analyze large datasets, design and implement fraud decisioning capabilities, partner with risk modeling and cross-functional teams, build KPI monitoring and automation, and communicate findings and project outcomes to senior leadership.

As a Quantitative Research Engineer, design, develop, and implement software for automated trading systems using advanced statistical techniques. Collaborate with researchers and prioritize business needs.

Lead a global analytics team to transform financial and operational data into actionable insights. Partner with stakeholders to align analytics with strategy, build scalable Power BI dashboards integrated with Snowflake, apply predictive modeling and ML, enforce data governance, drive automation with Python and Power Automate, and improve data architecture and reporting to inform decision-making and business performance.

The Ticketing Insights Analyst II analyzes complex ticketing data to improve operational efficiency and customer experience through automation and data storytelling while collaborating with various teams to drive insights.

The Data Specialist role involves analyzing complex data to improve supplier quality and performance using BI, statistical analysis, and machine learning. Responsibilities include maintaining dashboards, developing predictive models, and collaborating with teams to enhance decision-making and operational efficiency.

The Director of Business Development will define, negotiate, and secure partnerships to expand adMarketplace's search and performance advertising across various platforms while ensuring alignment with company goals and operational integration.

Lead end-to-end people analytics: frame problems, source and validate data, design methodologies, build advanced analytics/AI models, deliver executive-ready insights, partner with HR/Finance, and ensure data governance and privacy compliance.

Lead design, validation, and monitoring of fraud strategies using data analysis and AI/ML. Partner with product, technology, and operations to develop detection capabilities, test implementations, and balance fraud mitigation with revenue, cost, and customer impact.

Lead design and implementation of enterprise proactive monitoring rules to detect internal employee fraud. Use SAS and SQL to analyze large datasets, develop and evaluate rule logic, partner with stakeholders to deploy monitoring solutions, and support governance, audit readiness, and ongoing strategy enhancements.

Partner with Total Rewards stakeholders to design and execute analytics that evaluate employee wellbeing and benefits program ROI. Combine and validate data from claims, utilization, and other sources, build forecasting and advanced-analytics models, and deliver dashboards and executive summaries. Lead project workstreams, mentor junior analysts, and ensure data quality, compliance, and actionable insights to inform benefits strategy.

Support risk and analytics efforts by performing SQL/Python-based analysis, monitoring portfolio health, building scalable reports, collaborating cross-functionally, and integrating AI tools to surface insights that inform product, risk, and growth decisions.

Lead control and risk management for Data & Analytics products and platforms. Ensure adherence to the CORE program, embed AI/ML and data governance controls, manage Risk Assessment Structures, support control testing and issue remediation, develop control documentation, partner with Legal/Compliance/OpRisk/Audit, and support regulatory responses while leading and advising stakeholders.

Lead and build the Mortgage Model Development Center's mortgage data analytics capability end-to-end. Design scalable analytics frameworks across MBS/EMBS, loan performance, Intex, and loan-level datasets. Develop Python-based tools for ingestion, transformation, QC, cohort analysis, feature engineering, and mortgage analytics. Partner with model development, validation, investment portfolio, technology, and business stakeholders. Establish data quality standards, documentation, controls, production workflows, and drive adoption of AI-enabled workflows for extraction, anomaly detection, and analytics acceleration.

The Manager of Regulatory Submissions will lead regulatory strategies and submissions for global authorities, ensuring regulatory alignment with business goals while collaborating with cross-functional teams on medical devices.

Design, build, and productionize batch and streaming ETL/ELT pipelines and ML workflows on Azure Databricks. Implement Unity Catalog data products, MLflow model lifecycle controls, CI/CD for data/ML artifacts, and operational monitoring. Partner with cross-functional teams to modernize legacy workflows into scalable, production-ready solutions.

Develop, deploy, and monitor models and pattern-recognition algorithms to detect fraud across lending products. Write Python for analysis and modeling, query complex datasets with SQL, partner with Fraud Operations to refine features and reduce false positives/negatives, conduct ad hoc analyses, and communicate findings to support verification and underwriting improvements.

Lead data ownership and governance for wholesale credit risk. Define data strategies, ensure data quality, metadata and lineage, enable data products, mitigate data risks, and coordinate cross-functional delivery for analytics and reporting.

Drive card fraud strategy through data analysis, trend monitoring, and analytics-driven recommendations. Partner with product, technology, and operations to design, test, and implement detection and treatment solutions while balancing fraud mitigation, financial performance, customer experience, and operational efficiency.

Lead data ownership and governance for Corporate Finance and Treasury: define business data meaning, drive data strategy execution, improve data quality and controls, manage delivery timelines, mitigate data risks across the lifecycle, and support analytics by governing data used in analytics platforms.